[2023] 1z0-1110-22 All-in-One Exam Guide Practice To your 1z0-1110-22 Exam!
Preparations of 1z0-1110-22 Exam 2023 Oracle Cloud Infrastructure Unlimited 58 Questions
NEW QUESTION 24
You want to make your model more parsimonious to reduce the cost of collecting and processing dat a. You plan to do this by removing features that are highly correlated. You would like to create a heat map that displays the correlation so that you can identify candidate features to remove. Which Accelerated Data Science (ADS) SDK method would be appropriate to display the correlation between Continuous and Categorical features?
- A. Pearson_plot{}
- B. Corr{}
- C. Cramersv_plot{}
- D. Correlation_ratio_plot{}
Answer: D
NEW QUESTION 25
You are using a third-party Continuous Integration/Continuous Delivery (CI/CD) tool to create a pipeline for preparing and training models. How would you integrate a third-party tool outside Oracle Cloud Infrastructure (OCI) to access Data Science Jobs?
- A. Data Science Jobs does not accept code from third-party tools, therefore you need to run the pipeline externally.
- B. Third-party tools use authentication keys to create and run.
- C. Data Science Jobs Data Science Jobs is not accessible from outside OCI.
- D. Third-party software can access Data Science Jobs by using any of the OCI Software Development Kits (SDKs).
Answer: D
NEW QUESTION 26
You are a data scientist working inside a notebook session and you attempt to pip install a package from a public repository that is not included in your condo environment. After running this command, you get a network timeout error. What might be missing from your networking configuration?
- A. Primary Virtual Network Interface Card (VNIC).
- B. FastConnect to an on-premises network.
- C. Service Gateway with private subnet access.
- D. NAT Gateway with public internet access.
Answer: D
NEW QUESTION 27
You want to ensure that all stdout and stderr from your code are automatically collected and logged, without implementing additional logging in your code. How would you achieve this with Data Science Jobs?
- A. You can implement custom logging in your code by using the Data Science Jobs logging.
- B. Data Science Jots does not support automatic fog collection and storing.
- C. Make sure that your code is using the standard logging library and then store all the logs to Check Storage at the end of the job.
- D. On job creation, enable logging and select a log group. Then, select either log or the op-tion to enable automatic log creation.
Answer: A
NEW QUESTION 28
Where do calls to stdout and stderr from score.py go in a model deployment?
- A. The predict log in the Oracle Cloud Infrastructure (OCI) Logging service as defined in the deployment.
- B. The OCI Cloud Shell, which can be accessed from the console.
- C. The file that was defined for them on the Virtual stachine (VM).
- D. The OCI console.
Answer: A
NEW QUESTION 29
You are creating an Oracle Cloud Infrastructure (OCI) Data Science job that will run on a recurring basis in a production environment. This job will pick up sensitive data from an Object Storage bucket, train a model, and save it to the model catalog. How would you design the authentication mechanism for the job?
- A. Create a pre-authenticated request (PAA) for the Object Storage bucket, and use that in the job code.
- B. Use the resource principal of the job run as the signer in the job code, ensuring there is a dynamic group for this job run with appropriate access to Object Storage and the model catalog.
- C. Store your personal OCI config file and kays in the Vault, and access the Vault through the job nun resource principal
- D. Package your personal OC file and keys in the job artifact.
Answer: B
NEW QUESTION 30
You are working as a data scientist for a healthcare company. They decide to analyze the data to find patterns in a large volume of electronic medical records. You are asked to build a PySpark solution to analyze these records in a JupyterLab notebook. What is the order of recommended steps to develop a PySpark application in Oracle Cloud Infrastructure (OCI) Data Science?
- A. Install a spark conda environment. Configure core-site.xml. Launch a notebook session: Create a Data Flow application with the Accelerated Data Science (ADS) SOK. Develop your PySpark application
- B. Launch a notebook session. Install a PySpark conda environment. Configure coresite. xml.
- C. Configure core-site.xml. Install a PySPark conda environment. Create a Data Flow application with the Accelerated Data Science (ADS) SDK Develop your PySpark ap-plication. Launch a notebook session.
- D. Develop your PySpark application. Create a Data Flow application with the Ac-celerated Data science (ADS) SDK.
- E. Develop your PySpark application Create a Data Flow application with the Ac-celerated Data Science (ADS) SOK
- F. Launch a notebook session. Configure core-site.xml. Install a PySPark conda environ-ment.
Answer: D
NEW QUESTION 31
You are preparing a configuration object necessary to create a Data Flow application. Which THREE parameter values should you provide?
- A. The compartment of the Data Flow application.
- B. The display name of the application.
- C. The bucket used to read/write the pySpark script in Object Storage.
- D. The local path to your pySpark script.
- E. The path to the arhive.zip file.
Answer: B,C,D
NEW QUESTION 32
The feature type TechJob has the following registered validators: Tech-Job.validator.register(name='is_tech_job', handler=is_tech_job_default_handler) Tech-Job.validator.register(name='is_tech_job', handler= is_tech_job_open_handler, condi-tion=('job_family',)) TechJob.validator.register(name='is_tech_job', handler= is_tech_job_closed_handler, condition=('job_family': 'IT')) When you run is_tech_job(job_family='Engineering'), what does the feature type validator system do?
- A. Execute the is_tech_job_closed_handler handler.
- B. Execute the is_tech_job_default_handler sales handler.
- C. Throw an error because the system cannot determine which handler to run.
- D. Execute the is_tech_job_open_handler handler.
Answer: C
NEW QUESTION 33
You have trained three different models on your data set using Oracle AutoML. You want to visualize the behavior of each of the models, including the baseline model, on the test set. Which class should be used from the Accelerated Data Science (ADS) SDK to visually compare the models?
- A. ADS Evaluator
- B. ADS Explainer
- C. EvaluationMetrics
- D. ADSTuner
Answer: C
NEW QUESTION 34
You are a computer vision engineer building an image recognition model. You decide to use Oracle Data Labeling to annotate your image dat a. Which of the following THREE are possible ways to annotate an image in Data Labeling?
- A. Adding a single label to an image.
- B. Adding labels to an image using object detection, by drawing bounding boxes to an im-age.
- C. Adding multiple labels to an image.
- D. Adding labels to an image by drawing bounding box to an image, is not supported by Data Labeling
- E. Adding labels to image using semantic segmentation, by drawing multiple bounding boxes to an image.
Answer: A,B,C
NEW QUESTION 35
Using Oracle AutoML, you are tuning hyperparameters on a supported model class and have specified a time budget. AutoML terminates computation once the time budget is exhausted. What would you expect AutoML to return in case the time budget is exhausted before hy-perparameter tuning is completed?
- A. The last generated hyperparameter configuration is returned.
- B. A random hyperparameter configuration is returned.
- C. A hyperparameter configuration with a minimum learning rate is returned.
- D. The current best-known hyperparameter configuration is returned.
Answer: D
NEW QUESTION 36
When preparing your model artifact to save it to the Oracle Cloud Infrastructure (OCI) Data Science model catalog, you create a score.py file. What is the purpose of the score.py fie?
- A. Execute the inference logic code
- B. Define the inference server dependencies.
- C. Define the compute scaling strategy.
- D. Configure the deployment infrastructure.
Answer: D
NEW QUESTION 37
You have just received a new data set from a colleague. You want to quickly find out summary information about the data set, such as the types of features, total number of observations, and data distributions, Which Accelerated Data Science (ADS) SDK method from the AD&Dataset class would you use?
- A. Show_in_notebook{}
- B. To_xgb{}
- C. Show_corr{}
- D. Compute{}
Answer: A
NEW QUESTION 38
You are a data scientist leveraging Oracle Cloud Infrastructure (OCI) Data Science to create a model and need some additional python libraries for processing genome sequencing dat a. Which of the following THREE statements are correct with respect to installing additional Python libraries to process the data?
- A. You can install private or custom libraries from your own internal repositories
- B. You cannot install a library that's not preinstalled in the provided image
- C. You can only install libraries using yum and pip as a normal user
- D. OCI Data Science allows privileges in notebook sessions.
- E. You can install any open source package available in a publicly accessible Python Package Index (PyPI) repository
Answer: A,C,E
NEW QUESTION 39
You have a data set with fewer than 1000 observations, and you are using Oracle AutoML to build a classifier. While visualizing the results of each stage of the Oracle AutoML pipeline, you notice that no visualization has been generated for one of the stages. Which stage is not visualized?
- A. Hyperparameter tuning
- B. Adaptive sampling
- C. Feature selection
- D. Algorithm selection
Answer: B
NEW QUESTION 40
You have received machine learning model training code, without clear information about the optimal shape to run the training on. How would you proceed to identify the optimal compute shape for your model training that provides a balanced cost and processing time?
- A. Start with a random compute shape and monitor the utilization metrics and time required to finish the model training Perform model training optimizations and performance tests in advance to identify the right compute shape before running the model training as a job.
- B. Start with a smaller shape and monitor the utilization metrics and time required to complete the model training. If the compute shape is fully utilized, change to compute that has more resources and re-run the job. Repeat the process until the processing time does not improve.
- C. Start with the strangest compute shape Jobs support and monitor the Job Run metrics and time required to complete the model training. Tune the model so that it utilizes as much compute resources as possible, even at an increased cost.
- D. Start with a smaller shape and monitor the Job Run metrics and time required to complete the model training: If the compute shape is not fully utilized, tune the model parameters, and rerun the job. Repeat the process until the shape resources are fully utilized.
Answer: B
NEW QUESTION 41
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